Tensorflow Debug with CDT

git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow

sudo apt install python3-dev python3-pip
pip install -U --user pip six 'numpy<1.19.0' wheel setuptools mock 'future>=0.17.1' 'gast==0.3.3' typing_extensions
pip install -U --user keras_applications --no-deps
pip install -U --user keras_preprocessing --no-deps

./configure

sudo apt install curl gnupg
curl -fsSL https://bazel.build/bazel-release.pub.gpg | gpg --dearmor > bazel.gpg
sudo mv bazel.gpg /etc/apt/trusted.gpg.d/
echo "deb [arch=amd64] https://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
sudo apt update && sudo apt install bazel

 
bazel build --config=opt --copt -g //tensorflow/tools/lib_package:libtensorflow --verbose_failures
#You can also use --per_file_copt to allow only some library with debug info.
bazel build --config=opt  --per_file_copt=.*tensorflow.*@-g //tensorflow/tools/lib_package:libtensorflow --verbose_failures
 
[root@localhost conv_ops]# gdb conv_ops_3d.pic.o
GNU gdb (GDB) Red Hat Enterprise Linux 7.6.1-114.el7
Copyright (C) 2013 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.  Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-redhat-linux-gnu".
For bug reporting instructions, please see:
<http://www.gnu.org/software/gdb/bugs/>...
Reading symbols from /root/.cache/bazel/_bazel_root/e88dc1dcc3c90dfdeee7304faf39c313/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/core/kernels/_objs/conv_ops/conv_ops_3d.pic.o...done.
(gdb) 
 
#Other libraries may need for debuging.
bazel build --config=opt  --copt -g //tensorflow/cc:cc_ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/c:c_test_util --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/c:c_api --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:cc_ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:const_op --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:array_ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:match_ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:math_ops --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/cc:scope --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/core:test --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/core:testlib --verbose_failures
bazel build --config=opt  --copt -g //tensorflow/core/kernels:ops_testutil --verbose_failures

//============================================================================
// Name        : TensorflowTest.cpp
// Author      : 
// Version     :
// Copyright   : Your copyright notice
// Description : Hello World in C++, Ansi-style
//============================================================================
 
#include <iostream>
#include <tensorflow/c/c_api.h>
#include <tensorflow/c/c_test_util.h>
 
#include <algorithm>
#include <cstddef>
#include <iterator>
#include <memory>
#include <vector>
#include <string.h>
 
using namespace std;
 
int main() {
	cout << "!!!Hello World!!!" << endl; // prints !!!Hello World!!!
	cout << "Hello from TensorFlow C library version" << TF_Version() << endl;
 
	TF_Status* s = TF_NewStatus();
	TF_Graph* graph = TF_NewGraph();
 
	// Construct the graph: A + 2 + B
	TF_Operation* a = Placeholder(graph, s, "A");
	cout << TF_Message(s);
 
	TF_Operation* b = Placeholder(graph, s, "B");
	cout << TF_Message(s);
 
	TF_Operation* two = ScalarConst(2, graph, s);
	cout << TF_Message(s);
 
	TF_Operation* plus2 = Add(a, two, graph, s, "plus2");
	cout << TF_Message(s);
 
	TF_Operation* plusB = Add(plus2, b, graph, s, "plusB");
	cout << TF_Message(s);
 
	// Setup a session and a partial run handle.  The partial run will allow
	// computation of A + 2 + B in two phases (calls to TF_SessionPRun):
	// 1. Feed A and get (A+2)
	// 2. Feed B and get (A+2)+B
	TF_SessionOptions* opts = TF_NewSessionOptions();
	TF_Session* sess = TF_NewSession(graph, opts, s);
	TF_DeleteSessionOptions(opts);
 
	TF_Output feeds[] = { TF_Output { a, 0 }, TF_Output { b, 0 } };
	TF_Output fetches[] = { TF_Output { plus2, 0 }, TF_Output { plusB, 0 } };
 
	const char* handle = nullptr;
	TF_SessionPRunSetup(sess, feeds, TF_ARRAYSIZE(feeds), fetches,
			TF_ARRAYSIZE(fetches), NULL, 0, &handle, s);
	cout << TF_Message(s);
 
	// Feed A and fetch A + 2.
	TF_Output feeds1[] = { TF_Output { a, 0 } };
	TF_Output fetches1[] = { TF_Output { plus2, 0 } };
	TF_Tensor* feedValues1[] = { Int32Tensor(1) };
	TF_Tensor* fetchValues1[1];
	TF_SessionPRun(sess, handle, feeds1, feedValues1, 1, fetches1, fetchValues1,
			1, NULL, 0, s);
	cout << TF_Message(s);
	cout << *(static_cast<int*>(TF_TensorData(fetchValues1[0]))) << endl;
 
	// Clean up.
	TF_DeletePRunHandle(handle);
	TF_DeleteSession(sess, s);
	cout << TF_Message(s);
	TF_DeleteGraph(graph);
	TF_DeleteStatus(s);
	return 0;
}